Chen, L., Tang, W. and John, N.W., 2017. Real-time Geometry-Aware Augmented Reality in Minimally Invasive Surgery. Healthcare Technology Letters, 4 (5), 163-167.
Full text available as:
|
PDF (Author version)
AECAI -Long Chen.pdf - Accepted Version Available under License Creative Commons Attribution. 9MB | |
|
PDF (OPEN ACCESS VERSION)
HTL.2017.0068.pdf - Accepted Version Available under License Creative Commons Attribution. 9MB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
Official URL: http://digital-library.theiet.org/content/journals...
Abstract
The potential of Augmented Reality (AR) technology to assist minimally invasive surgeries (MIS) lies in its computational performanceand accuracy in dealing with challenging MIS scenes. Even with the latest hardware and software technologies, achieving both real-timeand accurate augmented information overlay in MIS is still a formidable task. In this paper, we present a novel real-time AR frameworkfor MIS that achieves interactive geometric aware augmented reality in endoscopic surgery with stereo views. Our framework tracks themovement of the endoscopic camera and simultaneously reconstructs a dense geometric mesh of the MIS scene. The movement of the camerais predicted by minimising the re-projection error to achieve a fast tracking performance, while the 3D mesh is incrementally built by a densezero mean normalised cross correlation stereo matching method to improve the accuracy of the surface reconstruction. Our proposed systemdoes not require any prior template or pre-operative scan and can infer the geometric information intra-operatively in real-time. With thegeometric information available, our proposed AR framework is able to interactively add annotations, localisation of tumors and vessels,and measurement labeling with greater precision and accuracy compared with the state of the art approaches.
Item Type: | Article |
---|---|
ISSN: | 2053-3713 |
Uncontrolled Keywords: | Augmented Reality ; Minimally Invasive Surgery |
Group: | Faculty of Science & Technology |
ID Code: | 29496 |
Deposited By: | Symplectic RT2 |
Deposited On: | 24 Jul 2017 11:31 |
Last Modified: | 14 Mar 2022 14:05 |
Downloads
Downloads per month over past year
Repository Staff Only - |